From the course: Python for AI Projects: From Data Exploration to Impact

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AI and machine learning (ML) frameworks

AI and machine learning (ML) frameworks - Python Tutorial

From the course: Python for AI Projects: From Data Exploration to Impact

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AI and machine learning (ML) frameworks

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- [Instructor] Now that we've explored how AI can power various use cases within our Explore California case study, it's time to dig deeper into the tools and standards that will help us build these AI systems efficiently and responsibly. Scikit-learn is a core Python library for building and evaluating ML models. It provides a simple interface to powerful tools for data, pre-processing and model training, all tightly integrated with the broader Python data ecosystem, which consists of libraries such as NumPy, Pandas, and Matplotlib amongst many others. We'll start by using some pre-built NLP methods available in scikit-learn, like TF-IDF Vectorization and stop word removal to kick off our text analysis. These are simple but powerful ways to get value out of raw text without needing an LLM. In our recommendations initiative for our Explore California case study, we'll be using traditional ML techniques to predict which…

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